Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 226 · 40 questions

AI tip (Show, label, learn): Machine learning learns patterns from many labelled examples — a label is the right answer tag on each example. Good for training: many varied examples, correct labels, every type the model will meet, and separate new data for testing. Bad for training: very few examples, wrong or random labels, only one kind of example, blurry examples, testing on the training data.

1. 1.True or false: the message “Happy birthday! See you at lunch” should be labelled “not spam”. (a) False (b) True
2. 2.True or false: “new data for testing” is good for training a model. (a) False (b) True
3. 3.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it may get it wrong (b) it will be perfect (c) it will shut down (d) it will turn yellow
4. 4.📚 Good or bad for training a model: testing on training data? (a) bad for training (b) good for training
5. 5.True or false: “wrong labels” is good for training a model. (a) True (b) False
6. 6.True or false: “wrong labels” is bad for training a model. (a) False (b) True
7. 7.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “not spam”. (a) True (b) False
8. 8.Which of these is good for training a model? (a) wrong labels (b) testing on training data (c) correct labels (d) copies of one photo
9. 9.📚 Good or bad for training a model: correct labels? (a) good for training (b) bad for training
10. 10.True or false: “copies of one photo” is bad for training a model. (a) False (b) True
11. 11.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “not spam”. (a) True (b) False
12. 12.🏷️ What is a “label” in machine learning? (a) a sticker on a laptop (b) the right answer tag (c) the font size (d) the price
13. 13.Which of these is good for training a model? (a) testing on training data (b) copies of one photo (c) only one kind of example (d) photos in many lights
14. 14.🐶 To teach a model to spot dogs in photos, what do you give it? (a) one single photo (b) a song about dogs (c) many labelled photos (d) a list of rules only
15. 15.📚 Good or bad for training a model: checking labels twice? (a) good for training (b) bad for training
16. 16.Which of these is bad for training a model? (a) correct labels (b) only one kind of example (c) clear, sharp examples (d) many varied examples
17. 17.Which of these is bad for training a model? (a) clear, sharp examples (b) many varied examples (c) new data for testing (d) testing on training data
18. 18.🔍 Which is the odd one out? (a) wrong labels (b) checking labels twice (c) new data for testing (d) clear, sharp examples
19. 19.🔍 Which is the odd one out? (a) copies of one photo (b) correct labels (c) blurry, unclear photos (d) only one kind of example
20. 20.🔍 Which is the odd one out? (a) correct labels (b) new data for testing (c) many varied examples (d) testing on training data
21. 21.Which of these is good for training a model? (a) very few examples (b) examples of every type (c) only one kind of example (d) copies of one photo
22. 22.True or false: the message “Science project groups are on the board” should be labelled “spam”. (a) False (b) True
23. 23.Which of these is good for training a model? (a) new data for testing (b) blurry, unclear photos (c) labels added at random (d) very few examples
24. 24.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “You won a free phone! Click now!” (a) not spam (b) spam
25. 25.True or false: “examples of every type” is bad for training a model. (a) True (b) False
26. 26.True or false: the message “Share your OTP to get cashback” should be labelled “not spam”. (a) True (b) False
27. 27.🔍 Which is the odd one out? (a) many varied examples (b) blurry, unclear photos (c) testing on training data (d) very few examples
28. 28.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your account is locked, pay ₹99 now” (a) not spam (b) spam
29. 29.📚 Good or bad for training a model: copies of one photo? (a) bad for training (b) good for training
30. 30.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your library book is due on Monday” (a) not spam (b) spam
31. 31.📚 Usually, more good examples make a model… (a) change colour (b) forget everything (c) better at its task (d) slower to switch on
32. 32.True or false: “many varied examples” is good for training a model. (a) False (b) True
33. 33.🔍 Which is the odd one out? (a) checking labels twice (b) photos in many lights (c) blurry, unclear photos (d) examples of every type
34. 34.Which of these is good for training a model? (a) testing on training data (b) clear, sharp examples (c) copies of one photo (d) very few examples
35. 35.🔍 Which is the odd one out? (a) checking labels twice (b) new data for testing (c) very few examples (d) correct labels
36. 36.True or false: “testing on training data” is bad for training a model. (a) True (b) False
37. 37.Which of these is bad for training a model? (a) examples of every type (b) checking labels twice (c) many varied examples (d) very few examples
38. 38.True or false: the message “Match practice moved to 5 pm” should be labelled “not spam”. (a) True (b) False
39. 39.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Last chance! Free gift card inside” (a) spam (b) not spam
40. 40.True or false: “photos in many lights” is bad for training a model. (a) True (b) False

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